README.md

In Jinsl-lab/SDImpute: SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data

SDImpute

A R package.

SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data

Introduction

SDImpute is an implement block imputation for dropout events in scRNA-seq data. SDImpute combines both cell-level and gene-level information to identify the drop-out events and borrows the information unaffected by dropouts from similar cells to impute the dropouts.

Installation

You can install SDImpute from GitHub with:

install.packages("devtools")         
library(devtools)           
install_github("Jinsl-lab/SDImpute")

Quick start

The input data of SDImpute is a gene expression matrix, columns and rows represent cells and genes respectively. You can choose whether or not to preprocess the data.

``` r library(SDImpute)

An example scRNA-seq dataset, containing 10,166 genes and 425 cells.

data(data) imputed_data<-SDImpute(data,do.nor=TRUE,do.log=FALSE,auto.k=FALSE,k=5,M=15,T=0.5)

Jinsl-lab/SDImpute documentation built on June 9, 2021, 9:12 a.m.